Serial Dependence

Serial Dependence is a statistical phenomenon in single-subject research designs wherein the current observation is systematically influenced by one or more preceding observations, thereby violating the assumption of data independence due to temporal autocorrelation.

583

Publications

57K

Citations

897

Authors

484

Institutions

Publications per year

2017–2026

145

Authors

897

  1. DW
    David Whitney

    University of California, Berkeley, United States

    14 publications · 2.3K citations

    14

    h-index

  2. CW
    Christian Weiß

    Helmut Schmidt University, Germany

    17 publications · 446 citations

    14

    h-index

  3. MH
    Marc Hallin

    Université Libre de Bruxelles, Belgium

    9 publications · 634 citations

    9

    h-index

  4. DC
    David C. Burr

    University of Florence, Italy

    9 publications · 849 citations

    9

    h-index

  5. MF
    Michele Fornaciai

    University of Massachusetts Amherst, United States

    9 publications · 588 citations

    9

    h-index

1–5 of 897

Venues

  1. Biometrika

    38 publications · 9.1K citations

    27

    h-index

  2. Journal of Vision

    26 publications · 1.7K citations

    20

    h-index

  3. Journal of the American Statistical Association

    23 publications · 1.5K citations

    18

    h-index

  4. Econometrica

    18 publications · 3.5K citations

    16

    h-index

  5. Journal of Econometrics

    12 publications · 1.2K citations

    12

    h-index

1–5